Adaptive self-tuning MTPA vector controller for IPMSM drive system

This paper presents an adaptive self-tuning maximum torque per ampere (MTPA) vector controller for an interior permanent-magnet synchronous motor (IPMSM) drive system. The control scheme consists of a synchronous frame decoupling current controller, MTPA torque controller, and adaptive parameter estimator. The estimator is applied to the q-axis current dynamics as the d-axis inductance can be assumed to be constant without loss of accuracy. Since the q-axis current dynamics is being disturbed by the magnet's back-EMF voltage, the proposed estimator is combined with a robust active-state decoupling scheme to ensure unbiased parameter estimate. The robust decoupling scheme is realized by estimating the magnet's flux linkage by a simple adaptation algorithm based on the steepest descent method. The system's model is greatly simplified when the robust decoupling scheme is combined with the q-axis current dynamics. Relying on the simplified model, a natural adaptive observer is used to estimate the q-axis current. Unknown motor parameters are estimated by minimizing the state estimation error using an iterative gradient algorithm offered by the affine projection. The estimated parameters are used for the self-tuning control. Experimental results are presented to demonstrate the validity and usefulness of the online parameter estimation and control loop tuning technique.     

Control-based reduction of pulsating torque for PMAC machines

Control methods in torque pulsating reduction for surface-mounted permanent magnet motors are discussed in this paper. The pulsating torque is a consequence of the nonsinusoidal flux-density distribution caused by the interaction of the rotor's permanent magnets with the changing stator reluctance. The proposed control method is estimator based. To assure parameter convergence, Lyapunov's direct method is used in estimator design for the flux Fourier's coefficients. A novel nonlinear torque controller based on flux/torque estimate is introduced to reduce the influence of the flux harmonics. The influence of the cogging torque is considerably reduced at lower motor speed using the internal model principle and adaptive feedforward compensation technique. The overall control scheme and experimental results are also presented     

Combined Flux Observer With Signal Injection Enhancement for Wide Speed Range Sensorless Direct Torque Control of IPMSM Drives

This paper proposes a motion-sensorless control system using direct torque control with space vector modulation for interior permanent magnet synchronous motor (IPMSM) drives, for wide speed range operation, including standstill. A novel stator flux observer with variable structure uses a combined voltage-current model with PI compensator for low-speed operations. As speed increases, the observer switches gradually to a PI compensated closed-loop voltage model, which is solely used at high speeds. High-frequency rotating-voltage injection with a single D-module bandpass vector filter and a phase-locked loop state observer with a new synchronization procedure are used to estimate the rotor position, which is needed only by the current model in stator flux observer at low speeds. A new rotor speed estimator for the whole speed-loop range, based on the stator flux speed estimation with a new dynamic correction depending on estimated torque, is proposed and tested. Extensive simulation results and significant experimental results provided good performance for the proposed IPMSM sensorless system in more than 1:1000 speed range, under full-load operation, from very low speeds (1 r/min experimental) up to rated speed.     

A Current Control Scheme With an Adaptive Internal Model for Torque Ripple Minimization and Robust Current Regulation in PMSM Drive Systems

This paper addresses the problem of uncertainties in practical permanent magnet synchronous motors (PMSMs), and proposes a simple adaptive internal model within the current feedback and reference current generation structure as a solution. Due to the time varying nature and the high-bandwidth property of uncertainties in a practical PMSM drive system, the internal model is simply chosen as the estimated uncertainty function. To provide a high bandwidth estimate of the uncertainty function with high-noise immunity, a simple adaptation law is derived, in the sense of Lyapunov functions, using the nominal current dynamics. The inclusion of the frequency modes of the disturbances to be eliminated (the flux harmonics and voltage disturbances caused by parameter variation) in the stable closed-loop system introduces very high-attenuation at different frequency modes corresponding to uncertainty modes. Therefore, a robust torque ripple minimization and current regulation performances are yielded. To properly tune the proposed scheme, a stability analysis based on a discrete-time Lyapunov function has been used to determine the stability limits of the adaptation gain. Comparative evaluation results are presented to demonstrate the effectiveness of the proposed control scheme under different operating conditions.     

Real-Time Speed and Flux Adaptive Control of Induction Motors Using Unknown Time-Varying Rotor Resistance and Load Torque

In this paper, an algorithm for direct speed and flux adaptive control of induction motors using unknown time-varying rotor resistance and load torque is described and validated with experimental results. This method is based on the variable structure theories and is potentially useful for adjusting online the induction motor controller unknown parameters (load torque and rotor resistance). The presented nonlinear compensator provides voltage inputs on the basis of rotor speed and stator current measurements, and generates estimates for both the unknown parameters and the nonmeasurable state variables (rotor flux and derivatives of the stator current and voltage) that converge to the corresponding true values. Experiments show that the proposed method achieved very good tracking performance within a wide range of the operation of the induction motor (with online variation of the rotor resistance: up to (87%). This high tracking performance of the rotor resistance variation demonstrates that the proposed adaptive control is beneficial for motor efficiency. The proposed algorithm also presented high decoupling performance and very interesting robustness properties with respect to the variation of the stator resistance (up to 100%), measurement noise, modeling errors, discretization effects, and parameter uncertainties (e.g., inaccuracies on motor inductance values). The other interesting feature of the proposed method is that it is simple and easily implementable in real time. Comparative results have shown that the proposed adaptive control decouples speed and flux tracking while standard field-oriented control does not.      

Comparative study of various artificial intelligence approaches applied to direct torque control of induction motor drives

In this paper, three intelligent approaches were proposed, applied to direct torque control (DTC) of induction motor drive to replace conventional hysteresis comparators and selection table, namely fuzzy logic, artificial neural network and adaptive neuro-fuzzy inference system (ANFIS). The simulated results obtained demonstrate the feasibility of the adaptive network-based fuzzy inference system based direct torque control (ANFIS-DTC). Compared with the classical direct torque control, fuzzy logic based direct torque control (FL-DTC), and neural networks based direct torque control (NN-DTC), the proposed ANFIS-based scheme optimizes the electromagnetic torque and stator flux ripples, and incurs much shorter execution times and hence the errors caused by control time delays are minimized. The validity of the proposed methods is confirmed by simulation results.     

Robust SVM-direct torque control of induction motor based on sliding mode controller and sliding mode observer

This paper proposes a design of control and estimation strategy for induction motor based on the variable structure approach. It describes a coupling of sliding mode direct torque control (DTC) with sliding mode flux and speed observer. This algorithm uses direct torque control basics and the sliding mode approach. A robust electromagnetic torque and flux controllers are designed to overcome the conventional SVM-DTC drawbacks and to ensure fast response and full reference tracking with desired dynamic behavior and low ripple level. The sliding mode controller is used to generate reference voltages in stationary frame and give them to the controlled motor after modulation by a space vector modulation (SVM) inverter. The second aim of this paper is to design a sliding mode speed/flux observer which can improve the control performances by using a sensorless algorithm to get an accurate estimation, and consequently, increase the reliability of the system and decrease the cost of using sensors. The effectiveness of the whole composed control algorithm is investigated in different robustness tests with simulation using Matlab/Simulink and verified by real time experimental implementation based on dS pace 1104 board.     

非对称中点钳位型逆变电路的开关磁阻电机模型预测直接转矩控制方法

针对开关磁阻电机(SRM)转矩脉动过大的问题,提出一种非对称中点钳位型逆变电路的模型预测直接转矩控制方法,该控制方法基于开关磁阻电机的电感特性及转矩产生原理对扇区进行重新划分,对非对称中点钳位型逆变电路的基本工作模式进行分析并选取基本电压状态,根据直接转矩控制原理及扇区实际意义制定新型矢量选择方案,减少每个控制周期中的预测状态数;在每个采样时刻求解基于离散时间非线性预测模型的最优控制问题来抑制转矩脉动。在Matlab/Simulink环境下搭建电机仿真模型,与直接转矩控制对比仿真结果表明,该控制方法对开关磁阻电机具有更好的调节效果.能有效抑制转矩脉动。     

VSC-based direct torque and reactive power control of doubly fed induction generator

This paper proposes a novel direct torque and reactive power control (DTC) for grid-connected doubly fed induction generators (DFIGs) in the wind power generation applications. The proposed DTC strategy employs a variable structure control (VSC) scheme to calculate the required rotor control voltage directly and to eliminate the instantaneous errors of active and reactive powers without involving any synchronous coordinate transformations, which essentially enhances the transient performance. Constant switching frequency is achieved as well by using space vector modulation (SVM), which eases the designs of power converter and ac harmonic filters. Simulated results on a 2 MW grid-connected DFIG system are presented and compared with those of the classic voltage-oriented vector control (VC) and traditional look-up-table (LUT) direct power control (DPC). The proposed VSC DTC maintains enhanced transient performance similar to the LUT DPC and keeps the steady-state harmonic spectra at the identical level as the VC strategy when the network is strictly balanced. Besides, the VSC DTC strategy is capable of fully eliminating the double-frequency pulsations in both the electromagnetic torque and the stator reactive power during network voltage unbalance.     

内置式永磁同步电机12扇区直接转矩控制方法

以电压矢量的最大利用率为基础引入12扇区控制方法,该方法细化矢量选择和扇区划分,增加可供选择的电压矢量数目,有效发挥了电压矢量对磁链和转矩的控制优势;研究变化的内滞环带对转矩脉动的影响,仿真结果表明相对于传统的6扇区直接转矩控制方式,该文引入的12扇区控制方法可明显减小转矩和磁链脉动,同时保留了传统的直接转矩控制中转矩动态响应迅速的特点;在不同操作条件(转速和转矩不同)下,进一步优化12扇区的控制效果。仿真结果验证了理论分析的正确性和所提出方法的可行性。     

A new sliding mode position controller with adaptive load torqueestimator for an induction motor

A new sliding mode control algorithm with an adaptive load torque estimator is presented to control the position of the induction motor in this paper. First, the rotor flux is estimated with the simplified rotor flux observer in the rotor reference frame and the feedback linearization theory is used to decouple the rotor position and the rotor flux amplitude. Then, a new sliding mode position controller with an adaptive load torque estimator is designed to control the position of the induction motor such that the chattering effects associated with the classical sliding mode position controller can be eliminated. Stability analysis is carried out using the Lyapunov stability theorem. Experimental results are presented to confirm the characteristics of the proposed approach. The good position tracking and load regulating responses can be obtained by the proposed position controller     

Passivity-based sliding mode position control for induction motor drives

In this paper, a passivity-based sliding-mode controller is proposed to control the motion of an induction motor. At first, the induction motor is proved to be a state strictly passive system. Then, a sliding-mode position controller with an adaptive load torque estimator is designed to control the position of the induction motor such that the chattering effects associated with a classical sliding-mode position controller can be eliminated. The stability analysis of the overall position control system is carried out by the passivity theory. The proposed approach is robust with regard to variations of motor mechanical parameters and load torque disturbances. Finally, experimental results are included to demonstrate that good position tracking can be obtained without the rotor flux observer.     

Compositive adaptive position control of induction motors based onpassivity theory

A passivity-based composite adaptive position control scheme for an induction motor is proposed in this paper. First, the dynamics of the induction motor are proved to be state strictly passive, and a composite adaptation algorithm is proposed to control the position of the induction motor. Then, the global stability of the induction motor position control system is formally proved by the passivity theory. Experimental results are provided to show that the good position tracking can be obtained without any information of the rotor flux. The proposed approach is robust to the variations of motor mechanical parameters and external load disturbances     

游梁式抽油机异步电动机矢量空间节能研究

提出游梁式抽油机异步电动机矢量控制最小励磁电流控制规律，对取得定子电流最小值的方法进行了证明。该节能控制方案不增加系统硬件成本，根据电动机的负载状态对励磁电流进行调节，使定子电流达到最小值，从而达到电动机自身节能的目的。基于MATLAB／SIMULINK仿真软件进行仿真研究，结果表明本文控制方案不仅能使游梁式抽油机异步电动机轻载运行时节能，还使其电磁转矩振荡减小。该控制方法可以推广到一般中小容量异步电动机变频调速系统。     

Closed loop torque SVM-DTC based on robust super twisting speed controller for induction motor drive with efficiency optimization

This paper presents a space vector modulation (SVM) based Direct Torque Control strategy (DTC) for induction motor (IM) in order to overcome the drawbacks of the classical DTC. SVM can reduce the high torque and flux ripples by preserving a fixed switching frequency. This technique is known by the closed loop torque SVM-DTC. Moreover, the control scheme performance is improved by inserting a second order sliding mode super twisting controller in the outer loop for speed regulation. This nonlinear technique ensures a good dynamic and high robustness against external disturbance. Furthermore, the IM energy optimization is treated in the second objective of this paper. A proposed model based loss minimization strategy is presented for efficiency optimization. This strategy chooses an optimal flux magnitude for each applied load torque. The proposed optimized SVM-DTC algorithm will be investigated by simulation and real time implementation using Matlab/Simulink with real time interface based on dSpace 1104 signal card.     

A new induction motor drive based on the flux vector acceleration method

A novel control strategy for the induction motor drive, based on the field acceleration method, is presented. The torque is controlled through variations of the stator flux angular velocity. The stator flux is controlled by using a feedforward control scheme, with the stator flux reference vector adjusted so as to obtain the fixed rotor flux amplitude. The applied controller assures a fast torque response, low torque ripple in the steady state, and drive operation with a constant switching frequency. The algorithm includes the improved stator and rotor flux estimation that guarantees the stable drive operation in all operating conditions, even at low speeds. The experimental tests verify the performance of the proposed algorithm, proving that good behavior of the drive is achieved in the transient and steady-state operating conditions.     

A novel NN based rotor flux MRAS to overcome low speed problems for rotor resistance estimation in vector controlled IM drives

This paper presents a new neural network based model reference adaptive system (MRAS) to solve low speed problems for estimating rotor resistance in vector control of induction motor (IM). The MRAS using rotor flux as the state variable with a two layer online trained neural network rotor flux estimator as the adaptive model (FLUX-MRAS) for rotor resistance estimation is popularly used in vector control. In this scheme, the reference model used is the flux estimator using voltage model equations. The voltage model encounters major drawbacks at low speeds, namely, integrator drift and stator resistance variation problems. These lead to a significant error in the estimation of rotor resistance at low speed. To address these problems, an offline trained NN with data incorporating stator resistance variation is proposed to estimate flux, and used instead of the voltage model. The offline trained NN, modeled using the cascade neural network, is used as a reference model instead of the voltage model to form a new scheme named as “NN-FLUXMRAS.” The NN-FLUX-MRAS uses two neural networks, namely, offline trained NN as the reference model and online trained NN as the adaptive model. The performance of the novel NN-FLUX-MRAS is compared with the FLUX-MRAS for low speed problems in terms of integral square error (ISE), integral time square error (ITSE), integral absolute error (IAE) and integral time absolute error (ITAE). The proposed NN-FLUX-MRAS is shown to overcome the low speed problems in Matlab simulation.     

皮带输送机永磁同步电机系统仿真分析

针对矿用运输设备皮带输送机永磁同步电机的现状,分析了矢量控制、直接转矩控制、自适应控制、滑模变控制和预测控制5种调速系统定向形式的优缺点。同时,利用MATLAB仿真模拟软件对永磁同步电机系统进行了仿真模拟,得出前馈解耦控制转速响应下的转速反应更加灵敏,解决了PI控制转速响应下转矩脉动问题,系统的稳定性得到了提高。综合利用多种控制方法可以实现对电机电流稳定性的控制和系统模块的预测,为皮带输送机适应不同工作环境提供了便利。     

A direct torque-controlled interior permanent-magnet synchronous motor drive without a speed sensor

This paper reports results of further investigation of the so-called direct torque control (DTC) technique to an interior permanent magnet (IPM) synchronous motor drive. This torque control technique for IPM motors requires no dq-axes current controllers and coordinate transformation networks. A completely sensorless IPM motor drive with DTC, which uses a new speed estimator from the stator flux linkage vector and the torque angle, is presented. It is shown that including the torque angle in the estimation process results in a far more accurate transient speed estimator than what is reported in the existing literature.     

Induction motor dynamic and static inductance identification usinga broadband excitation technique

The performance of indirect vector control depends upon accurate prediction of the motor slip angular frequency (ω_s) for the demand torque. The required slip gain depends upon the rotor time constant of the motor (T_r). This value varies significantly over the operating temperature range and saturation level of a typical motor. This variation, if not compensated for, results in a significant degradation in torque production from a vector control system. The saturation effect can be compensated by an adaptive flux model if precise knowledge of the induction motor magnetizing curve is available. The aim of this paper is to present the application of an advanced system identification methodology enabling the off-line estimation of the magnetizing curve (dynamic and static inductance) of induction motors